#!/bin/python3
import pandas as pd
import numpy as np
from argparse import ArgumentParser

def wrap_types(val):
    if np.isnan(val):
        print("NaN FOUND")
        val = "NULL"
    if type(val) in [str, pd._libs.tslibs.timestamps.Timestamp]:
        return f"'{val}'"
    else:
        return val

p = ArgumentParser()
# action store_true is for flags
p.add_argument("-i", "--input", nargs="+", help="Path to input excel file")
p.add_argument("-o", "--output", nargs="+", help="Path to output sql file")
args = p.parse_args()

if not args.input:
    in_file_path = input("Please enter path to input excel file: ")
else:
    in_file_path = args.input[0]

if not args.output:
    out_file_path = input("Please enter path to output sql file: ")
else:
    out_file_path = args.output[0]


print(f'Input: {in_file_path}\nOutput: {out_file_path}')

in_file = pd.ExcelFile(in_file_path)
print(in_file.parse("Datei", skiprows=1).head())

with open(out_file_path, "w") as of:
    for sheet in in_file.sheet_names:
        curr_meta = in_file.parse(sheet, nrows=1, header=None)
        curr_sheet = in_file.parse(sheet, header=1)
        curr_meta = curr_meta[0][0].split("#")
        db = curr_meta[0]
        table_prefix = curr_meta[1]
        table_suffix = sheet
        # One line is one test subject/object
        for line in curr_sheet.iterrows():
            indices = line[1].index
            values = line[1].values
            cols = ""
            vals = ""
            for i in range(len(indices)):
                # print(type(values[i]), ": ", values[i])
                if i != 0:
                    cols += f", {indices[i]}"
                    vals += f", {wrap_types(values[i])}"
                else:
                    cols += f"{indices[i]}"
                    vals += f"{wrap_types(values[i])}"
            # INSERT INTO $DB.$TABLE ($COL1, $COL2, ...) VALUES ($VAL1, $VAL2, ...)
            of.write(f'INSERT INTO "{db}"."{table_prefix}.{table_suffix}" ({cols}) VALUES ({vals})\n')